CISER: Customized Institute Specific Search Engine for Retrieving Research Papers

dc.contributor.authorSankar, S.
dc.contributor.authorMuslihuddeen, H.
dc.contributor.authorOstwal, S.
dc.contributor.authorSathvika, P.
dc.contributor.authorAnand Kumar, M.
dc.date.accessioned2026-02-06T06:35:05Z
dc.date.issued2023
dc.description.abstractThis paper proposes a methodology of a search engine system for searching research papers customized to our institute students. Most of the courses are associated with course projects where students face difficulties in finding the best research papers associated with the course. So, here we propose a customized mechanism to search the research papers published by the faculties of the institute. The input for the proposed search engine can either be the course name or the topic itself. We give users two options: search by course name and topic. If the course name is given as input, we get the corresponding keywords for the course, and then we implement semantic similarity on the Author Keywords. If the user searches by topic, we perform semantic similarity using the given topic and the Author Keywords of the research papers. We have also created a web interface using Django. © 2023 IEEE.
dc.identifier.citation2023 International Conference on Innovative Trends in Information Technology, ICITIIT 2023, 2023, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/ICITIIT57246.2023.10068620
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/29623
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectBERT Model
dc.subjectCosine similarity
dc.subjectDjango
dc.subjectSearch Engine
dc.subjectSemantic Similarity
dc.titleCISER: Customized Institute Specific Search Engine for Retrieving Research Papers

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